Exploratory toxicology as an integrated part of drug discovery. Part I: Why and how

1H NMR spectroscopic characterisation of HepG2 cells as a model metabolic system for toxicology studies

The immortalised human hepatocellular HepG2 cell line is commonly used for toxicology studies as an alternative to animal testing due to its characteristic liver-distinctive functions. However, little is known about the baseline metabolic changes within these cells upon toxin exposure. We have applied high-resolution 1H Nuclear Magnetic Resonance (NMR) spectroscopy to characterise the biochemical composition of HepG2 cells at baseline and post-exposure to hydrogen peroxide (H2O2). Metabolic profiles of live cells, cell extracts, and their spent media supernatants were obtained using 1H high-resolution magic angle spinning (HR-MAS) NMR and 1H NMR spectroscopic techniques. Orthogonal partial least squares discriminant analysis (O-PLS-DA) was used to characterise the metabolites that differed between the baseline and H2O2 treated groups. The results showed that H2O2 caused alterations to 10 metabolites, including acetate, glutamate, lipids, phosphocholine, and creatine in the live cells; 25 metabolites, including acetate, alanine, adenosine diphosphate (ADP), aspartate, citrate, creatine, glucose, glutamine, glutathione, and lactate in the cell extracts, and 22 metabolites, including acetate, alanine, formate, glucose, pyruvate, phenylalanine, threonine, tryptophan, tyrosine, and valine in the cell supernatants. At least 10 biochemical pathways associated with these metabolites were disrupted upon toxin exposure, including those involved in energy, lipid, and amino acid metabolism. Our findings illustrate the ability of NMR-based metabolic profiling of immortalised human cells to detect metabolic effects on central metabolism due to toxin exposure. The established data sets will enable more subtle biochemical changes in the HepG2 model cell system to be identified in future toxicity testing.

Enhancing scaffold-free spheroid models: 3D cell bioprinting method for metastatic HSC3-Oral squamous carcinoma cell line

3D in vitro systems offer advantages over the shortcomings of two-dimensional models by simulating the morphological and functional features of in vivo-like environments, such as cell-cell and cell-extracellular matrix interactions, as well as the co-culture of different cell types. Nevertheless, these systems present technical challenges that limit their potential in cancer research requiring cell line- and culture-dependent standardization. This protocol details the use of a magnetic 3D bioprinting method and other associated techniques (cytotoxicity assay and histological analysis) using oral squamous cell carcinoma cell line, HSC3, which offer advantages compared to existing widely used approaches. This protocol is particularly timely, as it validates magnetic bioprinting as a method for the rapid deployment of 3D cultures as a tool for compound screening and development of heterotypic cultures such as co-culture of oral squamous cell carcinoma cells with cancer-associated fibroblasts (HSC3/CAFs).

A novel in vitro high-content imaging assay for the prediction of drug-induced lung toxicity

The development of inhaled drugs for respiratory diseases is frequently impacted by lung pathology in non-clinical safety studies. To enable design of novel candidate drugs with the right safety profile, predictive in vitro lung toxicity assays are required that can be applied during drug discovery for early hazard identification and mitigation. Here, we describe a novel high-content imaging-based screening assay that allows for quantification of the tight junction protein occludin in A549 cells, as a model for lung epithelial barrier integrity. We assessed a set of compounds with a known lung safety profile, defined by clinical safety or non-clinical in vivo toxicology data, and were able to correctly identify 9 of 10 compounds with a respiratory safety risk and 9 of 9 compounds without a respiratory safety risk (90% sensitivity, 100% specificity). The assay was sensitive at relevant compound concentrations to influence medicinal chemistry optimization programs and, with an accessible cell model in a 96-well plate format, short protocol and application of automated imaging analysis algorithms, this assay can be readily integrated in routine discovery safety screening to identify and mitigate respiratory toxicity early during drug discovery. Interestingly, when we applied physiologically-based pharmacokinetic (PBPK) modelling to predict epithelial lining fluid exposures of the respiratory tract after inhalation, we found a robust correlation between in vitro occludin assay data and lung pathology in vivo, suggesting the assay can inform translational risk assessment for inhaled small molecules.

Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important Substructures

Predicting whether a compound can cause drug-induced liver injury (DILI) is difficult due to the complexity of drug mechanism. The cysteine trapping assay is a method for detecting reactive metabolites that bind to microsomes covalently. However, it is cumbersome to use 35S isotope-labeled cysteine for this assay. Therefore, we constructed an in silico classification model for predicting a positive/negative outcome in the cysteine trapping assay. We collected 475 compounds (436 in-house compounds and 39 publicly available drugs) based on experimental data performed in this study, and the composition of the results showed 248 positives and 227 negatives. Using a Message Passing Neural Network (MPNN) and Random Forest (RF) with extended connectivity fingerprint (ECFP) 4, we built machine learning models to predict the covalent binding risk of compounds. In the time-split dataset, AUC-ROC of MPNN and RF were 0.625 and 0.559 in the hold-out test, restrictively. This result suggests that the MPNN model has a higher predictivity than RF in the time-split dataset. Hence, we conclude that the in silico MPNN classification model for the cysteine trapping assay has a better predictive power. Furthermore, most of the substructures that contributed positively to the cysteine trapping assay were consistent with previous results.

Expanding Predictive Capacities in Toxicology: Insights from Hackathon-Enhanced Data and Model Aggregation

In the realm of predictive toxicology for small molecules, the applicability domain of QSAR models is often limited by the coverage of the chemical space in the training set. Consequently, classical models fail to provide reliable predictions for wide classes of molecules. However, the emergence of innovative data collection methods such as intensive hackathons have promise to quickly expand the available chemical space for model construction. Combined with algorithmic refinement methods, these tools can address the challenges of toxicity prediction, enhancing both the robustness and applicability of the corresponding models. This study aimed to investigate the roles of gradient boosting and strategic data aggregation in enhancing the predictivity ability of models for the toxicity of small organic molecules. We focused on evaluating the impact of incorporating fragment features and expanding the chemical space, facilitated by a comprehensive dataset procured in an open hackathon. We used gradient boosting techniques, accounting for critical features such as the structural fragments or functional groups often associated with manifestations of toxicity.

User-friendly microfluidic system reveals native-like morphological and transcriptomic phenotypes induced by shear stress in proximal tubule epithelium

Drug-induced nephrotoxicity is a leading cause of drug attrition, partly due to the limited relevance of pre-clinical models of the proximal tubule. Culturing proximal tubule epithelial cells (PTECs) under fluid flow to mimic physiological shear stress has been shown to improve select phenotypes, but existing flow systems are expensive and difficult to implement by non-experts in microfluidics. Here, we designed and fabricated an accessible and modular flow system for culturing PTECs under physiological shear stress, which induced native-like cuboidal morphology, downregulated pathways associated with hypoxia, stress, and injury, and upregulated xenobiotic metabolism pathways. We also compared the expression profiles of shear-dependent genes in our in vitro PTEC tissues to that of ex vivo proximal tubules and observed stronger clustering between ex vivo proximal tubules and PTECs under physiological shear stress relative to PTECs under negligible shear stress. Together, these data illustrate the utility of our user-friendly flow system and highlight the role of shear stress in promoting native-like morphological and transcriptomic phenotypes in PTECs in vitro, which is critical for developing more relevant pre-clinical models of the proximal tubule for drug screening or disease modeling.

Off target toxicities and links with physicochemical properties of medicinal products, including antibiotics, oligonucleotides, lipid nanoparticles (with cationic and/or anionic charges). Data review suggests an emerging pattern

Toxicology is an essential part of any drug development plan. Circumnavigating the risk of failure because of a toxicity issue can be a challenge, and failure in late development is extremely costly. To identify potential risks, it requires more than just understanding the biological target. The toxicologist needs to consider a compound's structure, it's physicochemical properties (including the impact of the overall formulation), as well as the biological target (e.g., receptor interactions). Understanding the impact of the physicochemical properties can be used to predict potential toxicities in advance by incorporating key endpoints in early screening strategies and/or used to compare toxicity profiles across lead candidates. This review discussed the risks of off-target and/or non-specific toxicities that may be associated with the physicochemical properties of compounds, especially those carrying dominant positive or negative charges, including amphiphilic small molecules, peptides, oligonucleotides and lipids/liposomes/lipid nanoparticles. The latter of which are being seen more and more in drug development, including the recent Covid pandemic, where mRNA and lipid nanoparticle technology is playing more of a role in vaccine development. The translation between non-clinical and clinical data is also considered, questioning how a physicochemical driven toxicity may be more universal across species, which means that such toxicity may be reassuringly translatable between species and as such, this information may also be considered as a support to the 3 R's, particularly in the early screening stages of a drug development plan.

The evolving role of investigative toxicology in the pharmaceutical industry

For decades, preclinical toxicology was essentially a descriptive discipline in which treatment-related effects were carefully reported and used as a basis to calculate safety margins for drug candidates. In recent years, however, technological advances have increasingly enabled researchers to gain insights into toxicity mechanisms, supporting greater understanding of species relevance and translatability to humans, prediction of safety events, mitigation of side effects and development of safety biomarkers. Consequently, investigative (or mechanistic) toxicology has been gaining momentum and is now a key capability in the pharmaceutical industry. Here, we provide an overview of the current status of the field using case studies and discuss the potential impact of ongoing technological developments, based on a survey of investigative toxicologists from 14 European-based medium-sized to large pharmaceutical companies.

Preclinical species gene expression database: Development and meta-analysis

The evaluation of toxicity in preclinical species is important for identifying potential safety liabilities of experimental medicines. Toxicology studies provide translational insight into potential adverse clinical findings, but data interpretation may be limited due to our understanding of cross-species biological differences. With the recent technological advances in sequencing and analyzing omics data, gene expression data can be used to predict cross species biological differences and improve experimental design and toxicology data interpretation. However, interpreting the translational significance of toxicogenomics analyses can pose a challenge due to the lack of comprehensive preclinical gene expression datasets. In this work, we performed RNA-sequencing across four preclinical species/strains widely used for safety assessment (CD1 mouse, Sprague Dawley rat, Beagle dog, and Cynomolgus monkey) in ∼50 relevant tissues/organs to establish a comprehensive preclinical gene expression body atlas for both males and females. In addition, we performed a meta-analysis across the large dataset to highlight species and tissue differences that may be relevant for drug safety analyses. Further, we made these databases available to the scientific community. This multi-species, tissue-, and sex-specific transcriptomic database should serve as a valuable resource to enable informed safety decision-making not only during drug development, but also in a variety of disciplines that use these preclinical species.

Involvement of the CYP1A1 inhibition-mediated activation of aryl hydrocarbon receptor in drug-induced hepatotoxicity

Hepatotoxicity is one of the most common toxicities observed in non-clinical safety studies of drug candidates, and it is important to understand the hepatotoxicity mechanism to assess the risk of drug-induced liver injury in humans. In this study, we investigated the mechanism of hepatotoxicity caused by 2-[2-Methyl-1-(oxan-4-yl)-1H-benzimidazol-5-yl]-1,3-benzoxazole (DSP-0640), a drug candidate that showed hepatotoxicity characterized by centrilobular hypertrophy and vacuolation of hepatocytes in a 4-week oral repeated-dose toxicity study in male rats. In the liver of rats treated with DSP-0640, the expression of aryl hydrocarbon receptor (AHR) target genes, including Cyp1a1, was upregulated. In in vitro reporter assays, however, DSP-0640 showed only minimal AHR-activating potency. Therefore, we investigated the possibility that DSP-0640 indirectly activated AHR by inhibiting the CYP1 enzyme-dependent clearance of endogenous AHR agonists. In in vitro assays, DSP-0640 showed inhibitory effects on both rat and human CYP1A1 and enhanced rat and human AHR-mediated reporter gene expression induced by 6-formylindolo[3,2-b]carbazole, a well-known endogenous AHR agonist. The possible involvement of CYP1A1 inhibition in AHR activation was also demonstrated with other hepatotoxic compounds tacrine and albendazole. These results suggest that CYP1A1 inhibition-mediated AHR activation is involved in the hepatotoxicity caused by DSP-0640 and that DSP-0640 might induce hepatotoxicity in humans as well. We propose that CYP1A1 inhibition-mediated AHR activation is a novel mechanism for drug-induced hepatotoxicity.

Application of Micro-Engineered Kidney, Liver, and Respiratory System Models to Accelerate Preclinical Drug Testing and Development

Developing novel drug formulations and progressing them to the clinical environment relies on preclinical in vitro studies and animal tests to evaluate efficacy and toxicity. However, these current techniques have failed to accurately predict the clinical success of new therapies with a high degree of certainty. The main reason for this failure is that conventional in vitro tissue models lack numerous physiological characteristics of human organs, such as biomechanical forces and biofluid flow. Moreover, animal models often fail to recapitulate the physiology, anatomy, and mechanisms of disease development in human. These shortfalls often lead to failure in drug development, with substantial time and money spent. To tackle this issue, organ-on-chip technology offers realistic in vitro human organ models that mimic the physiology of tissues, including biomechanical forces, stress, strain, cellular heterogeneity, and the interaction between multiple tissues and their simultaneous responses to a therapy. For the latter, complex networks of multiple-organ models are constructed together, known as multiple-organs-on-chip. Numerous studies have demonstrated successful application of organ-on-chips for drug testing, with results comparable to clinical outcomes. This review will summarize and critically evaluate these studies, with a focus on kidney, liver, and respiratory system-on-chip models, and will discuss their progress in their application as a preclinical drug-testing platform to determine in vitro drug toxicology, metabolism, and transport. Further, the advances in the design of these models for improving preclinical drug testing as well as the opportunities for future work will be discussed.

A new method for predicting the acute toxicity of carbamate pesticides based on the perspective of binding information with carrier protein

Toxicity is one of the most important factors limiting the success of new drug development. In this paper, we built a fast and convenient new method (Carrier protein binding information-toxicity relationship, CPBITR) for predicting drug acute toxicity based on the perspective of binding information with carrier protein. First, we studied the binding information between carbamate pesticides and human serum albumin (HSA) through various spectroscopic methods and molecular docking. Then a total of 16 models were established to clarify the relationship between binding information with HSA and drug toxicity. The results showed that the binding information was related to toxicity. Finally we obtained the effective toxicity prediction model for carbamate pesticides. And the "Platform for Predicting Drug Toxicity Based on the Information of Binding with Carrier Protein" was established with the Back-propagation neural network model. We proposed and proved that it was feasible to predict drug toxicity from this new perspective: binding with carrier protein. According to this new perspective, toxicity prediction model of other drugs can also be established. This new method has the advantages of convenience and fast, and can be used to screen out low-toxic drugs quickly in the early stage. It is helpful for drug research and development.

Non-synonymous alterations in AKR7A3 and ABCA6 correlate with bleeding in aged patients treated with rivaroxaban

Rivaroxaban is an oral anticoagulant that inhibits thrombin and blocks coagulation cascade through directly inactivating factors Xa. Despite rivaroxaban is widely used for prevention and treatment of venous thrombosis, and its common adverse reactions have been reported, including abnormal coagulation, mucosal hemorrhage, hematuria, and intracranial hemorrhage. To explore potential drivers of individual differences in adverse reactions induced by rivaroxaban, we performed whole‐exome sequencing and found that AKR7A3 rs1738023/rs1738025 and ABCA6 rs7212506 are susceptible sites for rivaroxaban‐related bleeding in aged patients treated with rivaroxaban. Gene functional annotation and signaling pathway enrichment indicated that homozygous mutations in AKR7A3 and ABCA6 might alter normal rivaroxaban transport and metabolism, and lead to continuous accumulation of activated drugs and toxic substances in vivo. Our results suggested that interindividual differences in bleeding events induced by rivaroxaban may be potentially driven by genetic alterations related to abnormal metabolism and transport of rivaroxaban.

Pseudocedrela kotschyi: a review of ethnomedicinal uses, pharmacology and phytochemistry

CONTEXT

Pseudocedrela kotschyi (Schweinf) Harms (Meliaceae) is an important medicinal plant found in tropical and subtropical countries of Africa. Traditionally, P. kotschyi is used in the treatment of various diseases including diabetes, malaria, abdominal pain and diarrhoea.

OBJECTIVE

To provide an overview of traditional medicinal claims, pharmacological properties, and phytochemical principles of P. kotschyi as a basis for its clinical applications and further research and development of new drugs.

METHODS

Through interpreting already published scientific manuscripts retrieved from different scientific search engines, namely, Medline, PubMed, EMBASE, Science Direct and Google scholar databases, an up-to-date review on the medicinal potentials of P. kotschyi from inception until September, 2020 was compiled. 'Pseudocedrela kotschyi', 'traditional uses', 'pharmacological properties' and 'chemical constituents' were used as search words.

RESULTS

At present, more than 30 chemical constituents have been isolated and identified from the root and stem bark of P. kotschyi, among which limonoids and triterpenes are the main active constituents. Based on prior research, P. kotschyi has been reported to possess anti-inflammatory, analgesic, antipyretic, anthelminthic, antimalaria, anti-leishmaniasis, anti-trypanosomiasis, hepatoprotective, antioxidant, antidiabetic, antidiarrheal, antimicrobial, and anticancer effects.

CONCLUSIONS

P. kotschyi is reported to be effective in treating a variety of diseases. Current phytochemical and pharmacological studies mainly focus on antimalaria, anti-leishmaniasis, anti-trypanosomiasis and anticancer potential of the root and stem bark of P. kotschyi. Although experimental data support the beneficial medicinal properties of this plant, there is still a paucity of information on its toxicity profile. Nonetheless, this review provides the basis for future research work.

Zebrafish toxicological screening could aid Leishmaniosis drug discovery

BACKGROUND

Recently a screen from a library of 1.8 million compounds identified in vitro a potent activity of the 2-aminobenzimidazoles series against Leishmania infantum, the etiological agent responsible by over 20.000 deaths each year. Several analogs were synthesized and in vitro tested through an optimization program, leading to a promising 2-aminobenzimidazoles derived compound (2amnbzl-d) that was progressed to in vivo mice studies. However, the not expected toxic effects prevented its progression to more advanced preclinical and clinical phases of drug development. Due to limitations of cell models in detecting whole organism complex interactions, 90% of the compounds submitted to pre-clinical tests are reproved. The use of Zebrafish embryo models could improve this rate, saving mammals, time and costs in the development of new drugs. To test this hypothesis, we compared 2amnbzl-d with two compounds with already established safety profile: carbamazepine and benznidazole, using an embryo Zebrafish platform based on acute toxicity, hepatotoxicity, neurotoxicity and cardiotoxicity assays (Pltf-AcHpNrCd).

RESULTS

Tests were performed blindly, and the results demonstrated the presence of lethal and teratogenic effects (CL50%: 14.8 µM; EC50%: 8.6 µM), hepatotoxic in concentrations above 7.5 µM and neurotoxic in embryos exposed to 15 µM of 2amnbzl-d. Nevertheless, benznidazole exposition showed no toxicity and only the 100 µM of carbamazepine induced a bradycardia.

CONCLUSIONS

Results using Pltf-AcHpNrCd with zebrafish reproduced that found in the toxicological tests with mammals to a portion of the costs and time of experimentation.

Retinoic acid-related orphan receptor gamma t (RORγt) inverse agonists/antagonists for the treatment of inflammatory diseases - where are we presently?

Introduction: The transcription factor retinoic acid-related orphan receptor gamma t (RORγt) has been identified as the master regulator of T_H17 cell differentiation and IL-17/22 production and is therefore an attractive target for the treatment of inflammatory diseases. Several orally or topically administered small molecule RORγt inverse agonists (RIAs) have progressed up to the end of clinical Phase 2.Areas covered: Based on publications and patent evaluations this review summarizes the evolution of the chemical matter for all 16 pharmaceutical companies, who develop(ed) a clinical-stage RIAs (until March 2021). Structure proposals for some clinical stage RIAs are presented and the outcome of the clinical trials is discussed.Expert opinion: So far, the clinical trials have been plagued with a high attrition rate. Main reasons were lack of efficacy (topical) or safety signals (oral) as well as, amongst other things, thymic lymphomas as seen with BMS-986251 in a preclinical study and liver enzyme elevations in humans with VTP-43742. Possibilities to mitigate these risks could be the use of RIAs with different chemical structures not interfering with thymocytes maturation and no livertox-inducing properties. With new frontrunners (e.g., ABBV-157 (cedirogant), BI 730357 or IMU-935) this is still an exciting time for this treatment approach.

Intra- and intercellular signaling pathways associated with drug-induced cardiac pathophysiology

Cardiac physiology and homeostasis are maintained by the interaction of multiple cell types, via both intra- and intercellular signaling pathways. Perturbations in these signaling pathways induced by oncology therapies can reduce cardiac function, ultimately leading to heart failure. As cancer survival increases, related cardiovascular complications are becoming increasingly prevalent, thus identifying the perturbations and cell signaling drivers of cardiotoxicity is increasingly important. Here, we discuss the homotypic and heterotypic cellular interactions that form the basis of intra- and intercellular cardiac signaling pathways, and how oncological agents disrupt these pathways, leading to heart failure. We also highlight the emerging systems biology techniques that can be applied, enabling a deeper understanding of the intra- and intercellular signaling pathways across multiple cell types associated with cardiovascular toxicity.

A high-throughput cell-based gaussia luciferase reporter assay for measurement of CYP1A1, CYP2B6, and CYP3A4 induction

The induction of cytochrome P450s can result in reduced drug efficacy and lead to potential drug-drug interactions. The xenoreceptors-aryl hydrocarbon receptor (AhR), constitutive androstane receptor (CAR), and pregnane X receptor (PXR)-play key roles in CYP induction by xenobiotics. In order to be able to rapidly screen for the induction of three enzymes (CYP1A1, CYP2B6, and CYP3A4), we generated a stable AhR-responsive HepG2 cell line, a stable CAR-responsive HepG2 cell line, and a stable PXR-responsive HepG2 cell line.To validate these stable xenoreceptor-responsive HepG2 cell lines, we evaluated the induction of the different Gaussia reporter activities, as well as the mRNA and protein expression levels of endogenous CYPs in response to different inducers.The induction of luciferase activity in the stable xenoreceptor-responsive HepG2 cell lines by specific inducers occurred in a concentration dependent manner. There was a positive correlation between the induction of luciferase activities and the induction endogenous CYP mRNA expression levels. These xenoreceptor-responsive HepG2 cell lines were further validated with known CYP1A1, CYP2B6, and CYP3A4 inducers.These stable xenoreceptor-responsive HepG2 cell lines may be used in preclinical research for the rapid and sensitive detection of AhR, CAR, and PXR ligands that induce CYP450 isoforms.

Synthesis and Characterization of the Novel Rodent-Active and CNS-Penetrant P2X7 Receptor Antagonist Lu AF27139

There remains an insufficient number of P2X7 receptor antagonists with adequate rodent potency, CNS permeability, and pharmacokinetic properties from which to evaluate CNS disease hypotheses preclinically. Herein, we describe the molecular pharmacology, safety, pharmacokinetics, and functional CNS target engagement of Lu AF27139, a novel rodent-active and CNS-penetrant P2X7 receptor antagonist. Lu AF27139 is highly selective and potent against rat, mouse, and human forms of the receptors. The rat pharmacokinetic profile is favorable with high oral bioavailability, modest clearance (0.79 L/(h kg)), and good CNS permeability. In vivo mouse CNS microdialysis studies of lipopolysaccharide (LPS)-primed and 2'(3')-O-(benzoylbenzoyl)adenosine-5'-triphosphate (BzATP)-induced IL-1β release demonstrate functional CNS target engagement. Importantly, Lu AF27139 was without effect in standard in vitro and in vivo toxicity studies. Based on these properties, we believe Lu AF27139 will be a valuable tool for probing the role of the P2X7 receptor in rodent models of CNS diseases.

Improving target assessment in biomedical research: the GOT-IT recommendations

Academic research plays a key role in identifying new drug targets, including understanding target biology and links between targets and disease states. To lead to new drugs, however, research must progress from purely academic exploration to the initiation of efforts to identify and test a drug candidate in clinical trials, which are typically conducted by the biopharma industry. This transition can be facilitated by a timely focus on target assessment aspects such as target-related safety issues, druggability and assayability, as well as the potential for target modulation to achieve differentiation from established therapies. Here, we present recommendations from the GOT-IT working group, which have been designed to support academic scientists and funders of translational research in identifying and prioritizing target assessment activities and in defining a critical path to reach scientific goals as well as goals related to licensing, partnering with industry or initiating clinical development programmes. Based on sets of guiding questions for different areas of target assessment, the GOT-IT framework is intended to stimulate academic scientists' awareness of factors that make translational research more robust and efficient, and to facilitate academia-industry collaboration.

Zebrafish as an Animal Model for Ocular Toxicity Testing: A Review of Ocular Anatomy and Functional Assays

Xenobiotics make their way into organisms from diverse sources including diet, medication, and pollution. Our understanding of ocular toxicities from xenobiotics in humans, livestock, and wildlife is growing thanks to laboratory animal models. Anatomy and physiology are conserved among vertebrate eyes, and studies with common mammalian preclinical species (rodent, dog) can predict human ocular toxicity. However, since the eye is susceptible to toxicities that may not involve a histological correlate, and these species rely heavily on smell and hearing to navigate their world, discovering visual deficits can be challenging with traditional animal models. Alternative models capable of identifying functional impacts on vision and requiring minimal amounts of chemical are valuable assets to toxicology. Human and zebrafish eyes are anatomically and functionally similar, and it has been reported that several common human ocular toxicants cause comparable toxicity in zebrafish. Vision develops rapidly in zebrafish; the tiny larvae rely on visual cues as early as 4 days, and behavioral responses to those cues can be monitored in high-throughput fashion. This article describes the comparative anatomy of the zebrafish eye, the notable differences from the mammalian eye, and presents practical applications of this underutilized model for assessment of ocular toxicity.

Single-Nuclei RNA Sequencing Assessment of the Hepatic Effects of 2,3,7,8-Tetrachlorodibenzo-p-dioxin

BACKGROUND AND AIMS

Characterization of cell specific transcriptional responses to hepatotoxicants is lost in the averages of bulk RNA-sequencing (RNA-seq). Single-cell/nuclei RNA-seq technologies enable the transcriptomes of individual cell (sub)types to be assessed within the context of in vivo models.

METHODS

Single-nuclei RNA-sequencing (snSeq) of frozen liver samples from male C57BL/6 mice gavaged with sesame oil vehicle or 30 μg/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) every 4 days for 28 days was used to demonstrate the application of snSeq for the evaluation of xenobiotics.

RESULTS

A total of 19,907 genes were detected across 16,015 nuclei from control and TCDD-treated livers. Eleven cell (sub)types reflected the expected cell diversity of the liver including distinct pericentral, midzonal, and periportal hepatocyte subpopulations. TCDD altered relative proportions of cell types and elicited cell-specific gene expression profiles. For example, macrophages increased from 0.5% to 24.7%, while neutrophils were only present in treated samples, consistent with histological evaluation. The number of differentially expressed genes (DEGs) in each cell type ranged from 122 (cholangiocytes) to 7625 (midcentral hepatocytes), and loosely correlated with the basal expression level of Ahr, the canonical mediator of TCDD and related compounds. In addition to the expected functions within each cell (sub)types, RAS signaling and related pathways were specifically enriched in nonparenchymal cells while metabolic process enrichment occurred primarily in hepatocytes. snSeq also identified the expansion of a Kupffer cell subtype highly expressing Gpnmb, as reported in a dietary NASH model.

CONCLUSIONS

We show that snSeq of frozen liver samples can be used to assess cell-specific transcriptional changes and population shifts in models of hepatotoxicity when examining freshly isolated cells is not feasible.

Use of a Bile Salt Export Pump Knockdown Rat Susceptibility Model to Interrogate Mechanism of Drug-Induced Liver Toxicity

Inhibition of the bile salt export pump (BSEP) may be associated with clinical drug-induced liver injury, but is poorly predicted by preclinical animal models. Here we present the development of a novel rat model using siRNA knockdown (KD) of Bsep that displayed differentially enhanced hepatotoxicity to 8 Bsep inhibitors and not to 3 Bsep noninhibitors when administered at maximally tolerated doses for 7 days. Bsep KD alone resulted in 3- and 4.5-fold increases in liver and plasma levels, respectively, of the sum of the 3 most prevalent taurine conjugated bile acids (T3-BA), approximately 90% decrease in plasma and liver glycocholic acid, and a distinct bile acid regulating gene expression pattern, without resulting in hepatotoxicity. Among the Bsep inhibitors, only asunaprevir and TAK-875 resulted in serum transaminase and total bilirubin increases associated with increases in plasma T3-BA that were enhanced by Bsep KD. Benzbromarone, lopinavir, and simeprevir caused smaller increases in plasma T3-BA, but did not result in hepatotoxicity in Bsep KD rats. Bosentan, cyclosporine A, and ritonavir, however, showed no enhancement of T3-BA in plasma in Bsep KD rats, as well as Bsep noninhibitors acetaminophen, MK-0974, or clarithromycin. T3-BA findings were further strengthened through monitoring TCA-d4 converted from cholic acid-d4 overcoming interanimal variability in endogenous bile acids. Bsep KD also altered liver and/or plasma levels of asunaprevir, TAK-875, TAK-875 acyl-glucuronide, benzbromarone, and bosentan. The Bsep KD rat model has revealed differences in the effects on bile acid homeostasis among Bsep inhibitors that can best be monitored using measures of T3-BA and TCA-d4 in plasma. However, the phenotype caused by Bsep inhibition is complex due to the involvement of several compensatory mechanisms.

Predictability of human pharmacokinetics of drugs that undergo hepatic organic anion transporting polypeptide (OATP)-mediated transport using single-species allometric scaling in chimeric mice with humanized liver: integration with hepatic drug metabolism

We previously reported a prediction method for human pharmacokinetics (PK) using single species allometric scaling (SSS) and the complex Dedrick plot in chimeric mice with humanized liver to predict the total clearance (CL_t), distribution volumes in steady state (Vd_ss) and plasma concentration-time profiles of several drugs metabolized by cytochrome P450 (P450) and non-P450 enzymes. In the present study, we examined eight compounds (bosentan, cerivastatin, fluvastatin, pitavastatin, pravastatin, repaglinide, rosuvastatin, valsartan) as typical organic anion transporting polypeptide (OATP) substrates and six compounds metabolized by P450 and non-P450 enzymes to evaluate the predictability of CL_t, Vd_ss and plasma concentration-time profiles after intravenous administration to chimeric mice. The predicted CL_t and Vd_ss of drugs that undergo OATP-mediated uptake and P450/non-P450-mediated metabolism reflected the observed data from humans within a threefold error range. We also examined the possibility of predicting plasma concentration-time profiles of drugs that undergo OATP-mediated uptake using the complex Dedrick plot in chimeric mice. Most profiles could be superimposed with observed profiles from humans within a two- to threefold error range. PK prediction using SSS and the complex Dedrick plot in chimeric mice can be useful for evaluating drugs that undergo both OATP-mediated uptake and P450/non-P450-mediated metabolism.

Opportunities for use of one species for longer-term toxicology testing during drug development: A cross-industry evaluation

An international expert working group representing 37 organisations (pharmaceutical/biotechnology companies, contract research organisations, academic institutions and regulatory bodies) collaborated in a data sharing exercise to evaluate the utility of two species within regulatory general toxicology studies. Anonymised data on 172 drug candidates (92 small molecules, 46 monoclonal antibodies, 15 recombinant proteins, 13 synthetic peptides and 6 antibody-drug conjugates) were submitted by 18 organisations. The use of one or two species across molecule types, the frequency for reduction to a single species within the package of general toxicology studies, and a comparison of target organ toxicities identified in each species in both short and longer-term studies were determined. Reduction to a single species for longer-term toxicity studies, as used for the development of biologicals (ICHS6(R1) guideline) was only applied for 8/133 drug candidates, but might have been possible for more, regardless of drug modality, as similar target organ toxicity profiles were identified in the short-term studies. However, definition and harmonisation around the criteria for similarity of toxicity profiles is needed to enable wider consideration of these principles. Analysis of a more robust dataset would be required to provide clear, evidence-based recommendations for expansion of these principles to small molecules or other modalities where two species toxicity testing is currently recommended.

Liver microphysiological systems development guidelines for safety risk assessment in the pharmaceutical industry

The liver is critical to consider during drug development because of its central role in the handling of xenobiotics, a process which often leads to localized and/or downstream tissue injury. Our ability to predict human clinical safety outcomes with animal testing is limited due to species differences in drug metabolism and disposition, while traditional human in vitro liver models often lack the necessary in vivo physiological fidelity. To address this, increasing numbers of liver microphysiological systems (MPS) are being developed, however the inconsistency in their optimization and characterization often leads to models that do not possess critical levels of baseline performance that is required for many pharmaceutical industry applications. Herein we provide a guidance on best approaches to benchmark liver MPS based on 3 stages of characterization that includes key performance metrics and a 20 compound safety test set. Additionally, we give an overview of frequently used liver injury safety assays, describe the ideal MPS model, and provide a perspective on currently best suited MPS contexts of use. This pharmaceutical industry guidance has been written to help MPS developers and end users identify what could be the most valuable models for safety risk assessment.

Today's Challenges to De-Risk and Predict Drug Safety in Human "Mind-the-Gap"

Current gaps in drug safety sciences can result from the inability (1) to identify hazard across multiple target organs, (2) to predict and risk assess with certainty against drug safety liabilities for the major target organs, (3) to optimally manage and mitigate against drug safety liabilities, and (4) to apply principles of governance on the generation, integration, and use of experimental data. Translational safety assessment to evaluate several target-organ drug toxicities can only be partially achieved by use of current in vitro and in vivo test systems. What remains to be tackled necessitates the deployment of in vitro-human-relevant test systems to address human specific or selective forms of toxicities. Nevertheless, such models may only address in part some of the requirements in today's armament of biomedical tools essential for improving the discovery of drug candidates. Refinement of in silico tools, Target Safety Assessment and a greater understanding of mechanistic insights of toxicities might provide future opportunities to better identify drug safety liabilities. The increasing diversity of drug modalities present further challenges for nonclinical and clinical development requiring further research to develop suitable test systems and technologies. Our ability to optimally manage and mitigate safety risk will come from the greater refinement of safety margin estimates, provision and use of human-relevant safety biomarkers, and understanding of the translation from in silico, in vitro, and in vivo studies to human. An improvement of governance frameworks and standards at all levels within organizations, national, and international, can only help facilitate drug discovery and development programs.

Learning important features from multi-view data to predict drug side effects

The problem of drug side effects is one of the most crucial issues in pharmacological development. As there are many limitations in current experimental and clinical methods for detecting side effects, a lot of computational algorithms have been developed to predict side effects with different types of drug information. However, there is still a lack of methods which could integrate heterogeneous data to predict side effects and select important features at the same time. Here, we propose a novel computational framework based on multi-view and multi-label learning for side effect prediction. Four different types of drug features are collected and graph model is constructed from each feature profile. After that, all the single view graphs are combined to regularize the linear regression functions which describe the relationships between drug features and side effect labels. L1 penalties are imposed on the regression coefficient matrices in order to select features relevant to side effects. Additionally, the correlations between side effect labels are also incorporated into the model by graph Laplacian regularization. The experimental results show that the proposed method could not only provide more accurate prediction for side effects but also select drug features related to side effects from heterogeneous data. Some case studies are also supplied to illustrate the utility of our method for prediction of drug side effects.

Use of Zebrafish in Drug Discovery Toxicology

Unpredicted human safety events in clinical trials for new drugs are costly in terms of human health and money. The drug discovery industry attempts to minimize those events with diligent preclinical safety testing. Current standard practices are good at preventing toxic compounds from being tested in the clinic; however, false negative preclinical toxicity results are still a reality. Continual improvement must be pursued in the preclinical realm. Higher-quality therapies can be brought forward with more information about potential toxicities and associated mechanisms. The zebrafish model is a bridge between in vitro assays and mammalian in vivo studies. This model is powerful in its breadth of application and tractability for research. In the past two decades, our understanding of disease biology and drug toxicity has grown significantly owing to thousands of studies on this tiny vertebrate. This Review summarizes challenges and strengths of the model, discusses the 3Rs value that it can deliver, highlights translatable and untranslatable biology, and brings together reports from recent studies with zebrafish focusing on new drug discovery toxicology.

Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions

Adverse drug effects (ADEs) are one of the leading causes of death in developed countries and are the main reason for drug recalls from the market, whereas the ADEs that are associated with action on the cardiovascular system are the most dangerous and widespread. The treatment of human diseases often requires the intake of several drugs, which can lead to undesirable drug-drug interactions (DDIs), thus causing an increase in the frequency and severity of ADEs. An evaluation of DDI-induced ADEs is a nontrivial task and requires numerous experimental and clinical studies. Therefore, we developed a computational approach to assess the cardiovascular ADEs of DDIs. This approach is based on the combined analysis of spontaneous reports (SRs) and predicted drug-target interactions to estimate the five cardiovascular ADEs that are induced by DDIs, namely, myocardial infarction, ischemic stroke, ventricular tachycardia, cardiac failure, and arterial hypertension. We applied a method based on least absolute shrinkage and selection operator (LASSO) logistic regression to SRs for the identification of interacting pairs of drugs causing corresponding ADEs, as well as noninteracting pairs of drugs. As a result, five datasets containing, on average, 3100 potentially ADE-causing and non-ADE-causing drug pairs were created. The obtained data, along with information on the interaction of drugs with 1553 human targets predicted by PASS Targets software, were used to create five classification models using the Random Forest method. The average area under the ROC curve of the obtained models, sensitivity, specificity and balanced accuracy were 0.837, 0.764, 0.754 and 0.759, respectively. The predicted drug targets were also used to hypothesize the potential mechanisms of DDI-induced ventricular tachycardia for the top-scoring drug pairs. The created five classification models can be used for the identification of drug combinations that are potentially the most or least dangerous for the cardiovascular system.

Use of precision cut lung slices as a translational model for the study of lung biology

Animal models remain invaluable for study of respiratory diseases, however, translation of data generated in genetically homogeneous animals housed in a clean and well-controlled environment does not necessarily provide insight to the human disease situation. In vitro human systems such as air liquid interface (ALI) cultures and organ-on-a-chip models have attempted to bridge the divide between animal models and human patients. However, although 3D in nature, these models struggle to recreate the architecture and complex cellularity of the airways and parenchyma, and therefore cannot mimic the complex cell-cell interactions in the lung. To address this issue, lung slices have emerged as a useful ex vivo tool for studying the respiratory responses to inflammatory stimuli, infection, and novel drug compounds. This review covers the practicality of precision cut lung slice (PCLS) generation and benefits of this ex vivo culture system in modeling human lung biology and disease pathogenesis.

[Application of novel 3D-bioprinted human liver tissue models in drug discovery research]

Primary human hepatocytes are widely used to study drug metabolism and enzyme induction. However, primary hepatocytes rapidly lose their hepatic function in conventional 2D cultures. Recently, a microphysiological system that overcomes this drawback has been actively investigated and applied in drug discovery research. Such novel in vitro models are desirable for the evaluation of the metabolic clearance of drugs with low turnover, drug-induced liver injury, and chronic liver diseases like liver fibrosis. This article reviews the characteristics and recent advances in 3D-bioprinted human liver tissue models in drug discovery research.

Response of safety pharmacologists to challenges arising from the rapidly evolving changes in the pharmaceutical industry

This commentary highlights and expands upon the thoughts conveyed in the lecture by Dr. Alan S. Bass, recipient of the 2017 Distinguished Service Award from the Safety Pharmacology Society, given on 27 September 2017 in Berlin, Germany. The lecture discussed the societal, scientific, technological, regulatory and economic events that dramatically impacted the pharmaceutical industry and ultimately led to significant changes in the strategic operations and practices of safety pharmacology. It focused on the emerging challenges and opportunities, and considered the lessons learned from drug failures and the influences of world events, including the financial crisis that ultimately led to a collapse of the world economies from which we are now recovering. Events such as these, which continue to today, challenge the assumptions that form the foundation of our discipline and dramatically affect the way that safety pharmacology is practiced. These include the latest scientific and technological developments contributing to the design and advancement of safe medicines. More broadly, they reflect the philosophical mission of safety pharmacology and the roles and responsibilities served by safety pharmacologists. As the discipline of Safety Pharmacology continues to evolve, develop and mature, the reader is invited to reflect on past experiences as a framework towards a vision of the future of the field.

Comparison of Quantitative and Qualitative (Q)SAR Models Created for the Prediction of Ki and IC50 Values of Antitarget Inhibitors

Estimation of interaction of drug-like compounds with antitargets is important for the assessment of possible toxic effects during drug development. Publicly available online databases provide data on the experimental results of chemical interactions with antitargets, which can be used for the creation of (Q)SAR models. The structures and experimental Ki and IC50 values for compounds tested on the inhibition of 30 antitargets from the ChEMBL 20 database were used. Data sets with Ki and IC50 values including more than 100 compounds were created for each antitarget. The (Q)SAR models were created by GUSAR software using quantitative neighborhoods of atoms (QNA), multilevel neighborhoods of atoms (MNA) descriptors, and self-consistent regression. The accuracy of (Q)SAR models was validated by the fivefold cross-validation procedure. The balanced accuracy was higher for qualitative SAR models (0.80 and 0.81 for Ki and IC50 values, respectively) than for quantitative QSAR models (0.73 and 0.76 for Ki and IC50 values, respectively). In most cases, sensitivity was higher for SAR models than for QSAR models, but specificity was higher for QSAR models. The mean R 2 and RMSE were 0.64 and 0.77 for Ki values and 0.59 and 0.73 for IC50 values, respectively. The number of compounds falling within the applicability domain was higher for SAR models than for the test sets.

Safety differentiation: emerging competitive edge in drug development

With increasing expectations to provide evidence of drug efficacy, safety, and cost-effectiveness, best-in-class drugs are a major value driver for the pharmaceutical industry. Superior safety is a key differentiation criterion that could be achieved through better risk:benefit profiles, safety margins, fewer contraindications, and improved patient compliance. To accomplish this, comparative safety assessments using innovative and adaptive nonclinical and clinical outcome-based approaches should be undertaken, and continuous strategic adjustments must be made as the risk:benefit profiles evolve. Key success criteria include scientific expertise and integration between all disciplines during the full extent of the drug development process.

A novel multi-parametric high content screening assay in ciPTEC-OAT1 to predict drug-induced nephrotoxicity during drug discovery

Drug-induced nephrotoxicity is a major concern in the clinic and hampers the use of available treatments as well as the development of innovative medicines. It is typically discovered late during drug development, which reflects a lack of in vitro nephrotoxicity assays available that can be employed readily in early drug discovery, to identify and hence steer away from the risk. Here, we report the development of a high content screening assay in ciPTEC-OAT1, a proximal tubular cell line that expresses several relevant renal transporters, using five fluorescent dyes to quantify cell health parameters. We used a validation set of 62 drugs, tested across a relevant concentration range compared to their exposure in humans, to develop a model that integrates multi-parametric data and drug exposure information, which identified most proximal tubular toxic drugs tested (sensitivity 75%) without any false positives (specificity 100%). Due to the relatively high throughput (straight-forward assay protocol, 96-well format, cost-effective) the assay is compatible with the needs in the early drug discovery setting to enable identification, quantification and subsequent mitigation of the risk for nephrotoxicity.

In vitro secondary pharmacological profiling: An IQ-DruSafe industry survey on current practices

INTRODUCTION

In 2015, IQ DruSafe conducted a survey of its membership to identify industry practices related to in vitro off target pharmacological profiling of small molecules.

METHODS

An anonymous survey of 20 questions was submitted to IQ-DruSafe representatives. Questions were designed to explore screening strategies, methods employed and experience of regulatory interactions related to in vitro secondary pharmacology profiling.

RESULTS

The pharmaceutical industry routinely utilizes panels of in vitro assays to detect undesirable off-target interactions of new chemical entities that are deployed at all stages of drug discovery and early development. The formats, approaches and size of panels vary between companies, in particular i) choice of assay technology; ii) test concentration (single vs. multiple concentrations) iii) rationale for targets and panels selection (taking into account organizational experience, primary target, therapeutic area, availability at service providers) iv) threshold level for significant interaction with a target and v) data interpretation. Data are generated during the early phases of drug discovery, principally before in vivo GLP studies (i.e., hit-to-lead, lead optimization, development candidate selection) and used to contextualize in vivo non-clinical and clinical findings. Data were included in regulatory documents, and around half of respondents experienced regulatory questions about the significance of the results.

CONCLUSION

While it seems that in vitro secondary pharmacological profiling is generally considered valuable across the industry, particularly as a tool in early phases of drug discovery for small molecules, there is only loose consensus on testing paradigm, the required interpretation and suitable follow up strategies to fully understand potential risk.

Understanding drug targets: no such thing as bad news

How can small-to-medium pharma and biotech companies enhance the chances of running a successful drug project and maximise the return on a limited number of assets? Having a full appreciation of the safety risks associated with proposed drug targets is a crucial element in understanding the unwanted side-effects that might stop a project in its tracks. Having this information is necessary to complement knowledge about the probable efficacy of a future drug. However, the lack of data-rich insight into drug-target safety is one of the major causes of drug-project failure today. Conducting comprehensive target-safety reviews early in the drug discovery process enables project teams to make the right decisions about which drug targets to take forward.

Moving beyond the comprehensive in vitro proarrhythmia assay: Use of human-induced pluripotent stem cell-derived cardiomyocytes to assess contractile effects associated with drug-induced structural cardiotoxicity

Drug-induced cardiotoxicity is a potentially severe side effect that can adversely affect myocardial contractility through structural or electrophysiological changes in cardiomyocytes. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are a promising human cardiac in vitro model system to assess both proarrhythmic and non-proarrhythmic cardiotoxicity of new drug candidates. The scalable differentiation of hiPSCs into cardiomyocytes provides a renewable cell source that overcomes species differences present in current animal models of drug toxicity testing. The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative represents a paradigm shift for proarrhythmic risk assessment, and hiPSC-CMs are an integral component of that paradigm. The recent advancements in hiPSC-CMs will not only impact safety decisions for possible drug-induced proarrhythmia, but should also facilitate risk assessment for non-proarrhythmic cardiotoxicity, where current non-clinical approaches are limited in detecting this risk before initiation of clinical trials. Importantly, emerging evidence strongly suggests that the use of hiPSC-CMs with cardiac physiological relevant measurements in vitro improves the detection of structural cardiotoxicity. Here we review high-throughput drug screening using the hiPSC-CM model as an experimentally feasible approach to assess potential contractile and structural cardiotoxicity in early phase drug development. We also suggest that the assessment of structural cardiotoxicity can be added to electrophysiological tests in the same platform to complement the Comprehensive in vitro Proarrhythmia Assay for regulatory use. Ideally, application of these novel tools in early drug development will allow for more reliable risk assessment and lead to more informed regulatory decisions in making safe and effective drugs available to the public.

[Contribution of chimeric mice with a humanized liver to the evaluation of pharmacology, toxicity, and pharmacokinetics in drug discovery and development]

To develop new drugs with high efficacy and safety, it is important to predict the pharmacological, toxicological, and pharmacokinetic profiles of drug candidates in humans. Chimeric mice with a humanized liver are mice in which human hepatocytes have been transplanted, such that mouse liver cells are replaced with human hepatocytes; these mice have been used as prediction models. Studies performed thus far indicate that chimeric mice with a humanized liver can be used for the prediction of human-specific metabolite formation and plasma concentration-time curves for several drugs. Furthermore, studies advocate the utility of chimeric mice with a humanized liver for modelling drug-induced hepatotoxicity and disease such as hepatitis virus infection in safety and pharmacological evaluations respectively. Taken together, these findings indicate that chimeric mice with a humanized liver can be used to evaluate the relationship between pharmacokinetics, toxicity, and efficacy; the contribution by active metabolites may also be assessed. In recent years, new and improved animal models have been developed to overcome the disadvantages of chimeric mice with a humanized liver. It is expected that their usefulness for optimization of drug candidates and translational research in drug discovery and development will further increase.

ADVERPred-Web Service for Prediction of Adverse Effects of Drugs

Application of structure-activity relationships (SARs) for the prediction of adverse effects of drugs (ADEs) has been reported in many published studies. Training sets for the creation of SAR models are usually based on drug label information which allows for the generation of data sets for many hundreds of drugs. Since many ADEs may not be related to drug consumption, one of the main problems in such studies is the quality of data on drug-ADE pairs obtained from labels. The information on ADEs may be included in three sections of the drug labels: "Boxed warning," "Warnings and Precautions," and "Adverse reactions." The first two sections, especially Boxed warning, usually contain the most frequent and severe ADEs that have either known or probable relationships to drug consumption. Using this information, we have created manually curated data sets for the five most frequent and severe ADEs: myocardial infarction, arrhythmia, cardiac failure, severe hepatotoxicity, and nephrotoxicity, with more than 850 drugs on average for each effect. The corresponding SARs were built with PASS (Prediction of Activity Spectra for Substances) software and had balanced accuracy values of 0.74, 0.7, 0.77, 0.67, and 0.75, respectively. They were implemented in a freely available ADVERPred web service ( http://www.way2drug.com/adverpred/ ), which enables a user to predict five ADEs based on the structural formula of compound. This web service can be applied for estimation of the corresponding ADEs for hits and lead compounds at the early stages of drug discovery.

A Round Trip from Medicinal Chemistry to Predictive Toxicology

Predictive toxicology is a new emerging multifaceted research field aimed at protecting human health and environment from risks posed by chemicals. Such issue is of extreme public relevance and requires a multidisciplinary approach where the experience in medicinal chemistry is of utmost importance. Herein, we will survey some basic recommendations to gather good data and then will review three recent case studies to show how strategies of ligand- and structure-based molecular design, widely applied in medicinal chemistry, can be adapted to meet the more restrictive scientific and regulatory goals of predictive toxicology. In particular, we will report: Docking-based classification models to predict the estrogenic potentials of chemicals. Predicting the bioconcentration factor using biokinetics descriptors. Modeling oral sub-chronic toxicity using a customized k-nearest neighbors (k-NN) approach.